Feature selection based on mutual information and redundancy-synergy coefficient.

Sheng Yang, Jun Gu
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引用次数: 12

Abstract

Mutual information is an important information measure for feature subset. In this paper, a hashing mechanism is proposed to calculate the mutual information on the feature subset. Redundancy-synergy coefficient, a novel redundancy and synergy measure of features to express the class feature, is defined by mutual information. The information maximization rule was applied to derive the heuristic feature subset selection method based on mutual information and redundancy-synergy coefficient. Our experiment results showed the good performance of the new feature selection method.

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基于互信息和冗余协同系数的特征选择。
互信息是特征子集的重要信息度量。本文提出了一种计算特征子集互信息的哈希机制。冗余协同系数是一种新的特征的冗余协同度量,通过互信息来表达类特征。利用信息最大化原则,导出了基于互信息和冗余协同系数的启发式特征子集选择方法。实验结果表明,新的特征选择方法具有良好的性能。
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